Click on Apply below to start your application. An initial review of applications will occur on July 1, 2026. Thereafter, applications will be reviewed on a rolling-basis throughout the 2026 calendar year, and selections made as projects for participation become available.

Immersive STEM Learning Fellowship: Real-World Data Network (RWDN)

The National Institutes of Health (NIH) Office of Data Science Strategy (ODSS) invites recent Postdocs to apply to a STEM learning fellowship focused on addressing the chronic disease crisis in America through innovative data science initiatives. NIH is establishing the Real-World Data Network (RWDN) to enable researchers to study predisposing factors, prevention strategies, treatment options, and long-term consequences of chronic diseases. To enhance this effort, NIH ODSS launched the Data COUNTS program, which promotes the collection, accessibility, and reuse of real-world data (RWD) from healthcare partners. Using privacy-preserving, federated approaches, Data COUNTS works to reduce data burden, improve transparency and quality, and accelerate access to evidence that informs biomedical research, public health, and regulatory needs.

What Will I Be Doing?

Through this fellowship, participants will engage in mentored learning opportunities to:

• Develop a foundational understanding of how NIH collaborates with healthcare organizations to advance real-world data collection.
• Build skills in evaluating data quality, exploring methodological approaches, and understanding data harmonization and governance within controlled-access environments.
• Apply clinical data science concepts to explore how researchers use RWD effectively across NIH programs.
• Gain experience engaging with HHS on RWD consent policies and sharing their research findings with NIH staff through white papers, posters and presentations.
• Learn how interdisciplinary teams—including experts in AI and clinical informatics—collaborate to shape funding opportunities and advance RWD initiatives.

Why Should I Apply?

This STEM learning fellowship offers participants the opportunity to expand their expertise in data science, clinical informatics, and NIH-led research initiatives. Participants will learn how NIH supports real-world data efforts, refine their analytical and methodological skills, and explore innovative approaches to tackling chronic diseases. Guided by experienced mentors, participants will contribute to impactful projects while gaining insights into how data-driven strategies can advance national health and biomedical research.

Where will I be located?

Fellows are expected to be fully engaged, either in-person or remote. In-person location is Bethesda, MD.

What financial provisions will I receive?

The selected candidates will receive a monthly stipend to help offset living and other expenses during this appointment. Stipend rates are determined by NIH officials and are based on the candidate’s academic and professional background. In addition, NIH may provide a health insurance supplement to cover the monthly premium costs if you elect the ORAU/ORISE health insurance plan, as necessary.

What is the length of the appointment?

The appointment will initially be for one year and may be renewed for up to an additional four years upon recommendation of NIH and is contingent on the availability of funds. 

When are selections made?

An initial review of applications will occur on July 1, 2026. Thereafter, applications will be reviewed on a rolling-basis throughout the 2026 calendar year, and selections made as projects for participation become available.

What is the Nature of the Appointment?

This program, administered by ORAU through its contract with the U.S. Department of Energy (DOE) to manage the Oak Ridge Institute for Science and Education (ORISE), was established through an interagency agreement between DOE and the National Institutes of Health (NIH). Participants do not become employees of NIH, DOE, ORISE, nor ORAU, and there are no employment-related benefits.

The qualified candidate must be 18 years or older at the time of application and should have received a doctoral degree in one of the relevant fields. The degree must have been received within the last five years of the appointment start date. Current graduate students who are nearing degree completion may apply but must have completed their degrees by the start of the fellowship.

Citizenship Requirements: This opportunity is available to U.S. citizens, Lawful Permanent Residents (LPR), and Foreign Nationals. Non-U.S. citizen applicants should refer to the Guidelines for Non-U.S. Citizens Details page for information about the valid immigration statuses that are acceptable for program participation.

A completed application consists of:

• A complete Zintellect profile.
• A program specific application submitted in Zintellect.
• Transcript(s) – Submit a copy of your most recent official transcript. For this opportunity, an unofficial transcript or copy of the student academic record printed by the applicant or by academic advisors from internal institution systems may be submitted to complete the application requirement, if you do not have a copy of your official transcript at the time of application. The transcript or academic record must include the name of the academic institution, name of the student, courses completed/in progress, grades and degree expected/awarded. A copy of your official transcript and/or letter showing proof of your degree may be required prior to starting the appointment. All transcripts must be in English or include an official English translation. 
• A current resume/CV, including academic history, employment history, relevant experiences, and publication list.
• One Recommendation - Applicants are required to provide contact information for at least one recommendation in order to submit the application, but up to three are encouraged. You are encouraged to request a recommendation from professionals who can speak to your abilities and potential for success, as well as your scientific capabilities and personal characteristics. Recommendation requests must be sent through the Zintellect application system. Recommenders will be asked to complete a recommendation in Zintellect. Recommendations submitted via email will not be accepted. Recommendations must be submitted before your application can be reviewed.

All documents submitted must be in English or include an official English translation. All social security numbers, student identification numbers, and/or dates of birth should be removed (blanked out or blackened out, made illegible, etc.) prior to uploading into the application system.

If you have questions, contact us at NIHprograms@orau.org. Please include the reference code NIH-DPCPSI-ODSS-DataCOUNTS-2026 for this opportunity in your email.

Connect with ORISE...on the GO! Download the new ORISE GO mobile app in the Apple App Store or Google Play Store to help you stay engaged, connected, and informed during your ORISE experience and beyond!

• Degree: Doctoral Degree received within the last 60 months or currently pursuing.
• Discipline(s):
  • Computer, Information, and Data Sciences (2 )
  • Life Health and Medical Sciences (5 )
• Age: Must be 18 years of age

I affirm that I have received my Doctoral degree within the last five years or am currently enrolled in a PhD program. If currently enrolled, I understand that my degree must be received before the appointment start date.